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Tunable phonon-driven magnon-magnon entanglement at room temperature

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arXiv 2022年

作者： Liu, Yuefei Bergman, Anders Bagrov, Andrey Delin, Anna Thonig, Danny Pereiro, Manuel Eriksson, Olle Streib, Simon Sjöqvist, Erik Azimi-Mousolou, Vahid Department of Applied Physics School of Engineering Sciences KTH Royal Institute of Technology AlbaNova University Center StockholmSE-10691 Sweden Department of Physics and Astronomy Uppsala University Box 516 UppsalaSE-751 20 Sweden Institute for Molecules and Materials Radboud University Heyendaalseweg 135 Nijmegen6525AJ Netherlands KTH Royal Institute of Technology StockholmSE-10044 Sweden School of Science and Technology Örebro University ÖrebroSE-701 82 Sweden Department of Applied Mathematics and Computer Science Faculty of Mathematics and Statistics University of Isfahan Isfahan81746-73441 Iran

We report the existence of entangled steady-states in bipartite quantum magnonic systems at elevated temperatures. We consider dissipative dynamics of two magnon modes in a bipartite antiferromagnet, subjected to interaction with a phonon mode and an external rotating magnetic field. To quantify the bipartite magnon-magnon entanglement, we use entanglement negativity and compute its dependence on temperature and magnetic field. We provide evidence that the coupling between magnon and phonon modes is necessary for the entanglement, and that, for any given phonon frequency and magnon-phonon coupling rate, there are always ranges of the magnetic field amplitudes and frequencies for which magnon-magnon entanglement persists at room temperature. Copyright © 2022, The Authors. All rights reserved.

关键词： Room temperature

Exploring the Non-Thermal Effects of Electromagnetic Field on Biological Structures: Importance of Experimental Design and Measurement Conditions

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SSRN

SSRN 2023年

作者： Bajtos, Marek Carnecka, Lucia Dang, Nhat Gurhan, Hakki Pobocikova, Ivana Radil, Roman Janousek, Ladislav The Department of Electromagnetic and Biomedical Engineering Faculty of Electrical Engineering and Information Technology University of Zilina Univerzitna 8215 Zilina010 26 Slovakia The Department of Electrical Computer and Energy Engineering The University of Colorado Boulder BoulderCO80309 United States The Ann and H.J. Smead Department of Aerospace Engineering Sciences College of Engineering and Applied Science University of Colorado Boulder BoulderCO80309 United States The Department of Applied Mathematics Faculty of Mechanical Engineering University of Zilina Univerzitna 8215 Zilina010 26 Slovakia

This study delves into the non-thermal effects of electromagnetic fields (EMF) on living organisms, emphasizing experimental design, precise measurements, and simulation verification. Grounded in Ion Parametric Resonance theory, it investigates the interaction between time-varying EMF and the Earth's geomagnetic field. The research comprises experiments assessing the Earth's magnetic field at various locations using a magnetometer. These measurements reveal variations influenced by location and surrounding metallic elements. Complementary simulations confirm these measurements and assess high-permeability metal shielding's effectiveness in reducing geomagnetic field fluctuations within the experimental area. Crucial findings arise from experiments involving 50 Hz EMF exposure on Saccharomyces cerevisiae yeasts for seven hours. Statistical analysis supports the impact on yeast cells and identifies an optimal shielding setup for future low-frequency EMF experiments. This research provides valuable insights into EMF's effects on organisms, enhances experimental precision, and guides EMF exposure shielding strategies. © 2023, The Authors. All rights reserved.

关键词： Yeast

"Self-Wiener" filtering: Data-driven deconvolution of deterministic signals

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arXiv 2020年

作者： Weiss, Amir Nadler, Boaz The Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States The Department of Computer Science and Applied Mathematics Faculty of Mathematics and Computer Science Weizmann Institute of Science 234 Herzl Street Rehovot7610001 Israel

We consider the problem of robust deconvolution, and particularly the recovery of an unknown deterministic signal convolved with a known filter and corrupted by additive noise. We present a novel, non-iterative data-driven approach. Specifically, our algorithm works in the frequency-domain, where it tries to mimic the optimal unrealizable non-linear Wiener-like filter as if the unknown deterministic signal were known. This leads to a threshold-type regularized estimator, where the threshold at each frequency is determined in a data-driven manner. We perform a theoretical analysis of our proposed estimator, and derive approximate formulas for its Mean Squared Error (MSE) at both low and high Signal-to-Noise Ratio (SNR) regimes. We show that in the low SNR regime our method provides enhanced noise suppression, and in the high SNR regime it approaches the optimal unrealizable solution. Further, as we demonstrate in simulations, our solution is highly suitable for (approximately) bandlimited or frequency-domain sparse signals, and provides a significant gain of several dBs relative to other methods in the resulting MSE. Copyright © 2020, The Authors. All rights reserved.

关键词： Mean square error

Adaptive Intelligent System for Monitoring and Control the Parameters of Pipelines Electrochemical Corrosion Protection

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Adaptive Intelligent System for Monitoring and Control the P...

2022 International Conference on Smart Information Systems and Technologies, SIST 2022

作者： Khussanov, Zhakhongir Prokhorov, Oleksandr Prokhorov, Valeriy Tevyashev, Andriy Turdybekova, Dilfuza Shatalov, Oleksii 'Structural And Biochemical Materials' M. Auezov South Kazakhstan University Regional Laboratory Of Engineering Shymkent Kazakhstan National Aerospace University 'Kharkiv Aviation Institute' Department Of Computer Science And Information Technologies Kharkiv Ukraine Natioanal University Of Radio Electronics Problematic Scientifically Adv. Lab. For Radio Monitoring And Proc. Of Radio Technical Information Kharkiv Ukraine National University Of Radio Electronics Department Of Applied Mathematics Kharkiv Ukraine M. Auezov South Kazakhstan University Shymkent Kazakhstan National University Of Radio Electronics Department Of Artificial Intelligence Kharkiv Ukraine

ISBN: (数字)9781665467902

ISBN: (纸本)9781665467902

The paper is dedicated to the creation of adaptive intelligent system that provides control and management of parameters of cathodic protection stations, taking into account changes in external conditions in some sections of pipelines. Multicriteria task of optimization of operation modes of cathodic protection stations is considered, as optimization is performed both by the criterion of optimality of protective potential distribution (uniformity of protective total potential distribution along the pipeline length) and by the criterion of minimum total protective current of stations. The system provides increase of reliability of electrochemical protection system as a whole and accordingly prevents possible emergencies at pipeline system, as well as reduces costs of current repair of pipelines, due to reliability and uninterrupted protection. © 2022 IEEE.

关键词： Adaptive control systems

Learning Nonlocal Sparse and Low-Rank Models for Image Compressive Sensing

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arXiv 2022年

作者： Zha, Zhiyuan Wen, Bihan Yuan, Xin Ravishankar, Saiprasad Zhou, Jiantao Zhu, Ce The School of Electrical & Electronic Engineering Nanyang Technological University Singapore639798 Singapore School of Engineering Westlake University Zhejiang Hangzhou310024 China The Department of Computational Mathematics Science and Engineering The Department of Biomedical Engineering Michigan State University East LansingMI48824 United States The State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science University of Macau 999078 China The School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China

The compressive sensing (CS) scheme exploits much fewer measurements than suggested by the Nyquist-Shannon sampling theorem to accurately reconstruct images, which has attracted considerable attention in the computational imaging community. While classic image CS schemes employ sparsity using analytical transforms or bases, the learning-based approaches have become increasingly popular in recent years. Such methods can effectively model the structure of image patches by optimizing their sparse representations or learning deep neural networks, while preserving the known or modeled sensing process. Beyond exploiting local image properties, advanced CS schemes adopt nonlocal image modeling, by extracting similar or highly correlated patches at different locations of an image to form a group to process jointly. More recent learning-based CS schemes apply nonlocal structured sparsity priors using group sparse (and related) representation (GSR) and/or low-rank (LR) modeling, which have demonstrated promising performance in various computational imaging and image processing applications. This article reviews some recent works in image CS tasks with a focus on the advanced GSR and LR based methods. Furthermore, we present a unified framework for incorporating various GSR and LR models and discuss the relationship between GSR and LR models. Finally, we discuss the open problems and future directions in the field. © 2022, CC BY.

关键词： Compressed sensing

Comparative study on atomic ionization in bicircular laser fields by length and velocity gauges S-matrix theory

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Chinese Physics B 2020年第2期29卷 254-261页

作者： Hong Xia Xin-Yan Jia Xiao-Lei Hao Li Guo Dai-He Fan Gen-Bai Chu Jing Chen School of Physical Science and Technology Southwest Jiaotong UniversityChengdu 610031China Institute of Theoretical Physics and Department of Physics Shanxi UniversityTaiyuan 030006China State Key Laboratory for Quantum Optics and Center for Cold Atom Physics Shanghai Institute of Optics and Fine MechanicsChinese Academy of SciencesShanghai 201800China Science and Technology on Plasma Physics Laboratory Laser Fusion Research CenterChina Academy of Engineering PhysicsMianyang 621900China HEDPS Center for Applied Physics and TechnologyPeking UniversityBeijing 100871China Institute of Applied Physics and Computational Mathematics Beijing 100088China

Ionization of atoms in counter-rotating and co-rotating bicircular laser fields is studied using the S-matrix theory in both length and velocity *** show that for both the bicircular fields,ionization rates are enhanced when the two circularly polarized lights have comparable *** addition,the curves of ionization rate versus the field amplitude ratio of the two colors for counter-rotating and co-rotating fields coincide with each other in the length gauge case at the total laser intensity 5×10^14 W/cm^2,which agrees with the experimental ***,the degree of the coincidence between the ionization rate curves of the two bicircular fields decreases with the increasing field amplitude ratio and decreasing total laser *** the help of the ADK theory,the above characteristics of the ionization rate curves can be well interpreted,which is related to the transition from the tunneling to multiphoton ionization mechanism.

关键词： above-threshold ionization(ATI) bicircular laser fields length gauge velocity gauge S-matrix theory

Design flaws and cryptanalysis of a standard mutual authentication protocol for cloud computing-based healthcare system

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Design flaws and cryptanalysis of a standard mutual authenti...

International Conference on Data sciences, Security and Applications, ICDSSA 2019

作者： Kumari, Adesh Abbasi, M. Yahya Kumar, Vinod Alam, Mansaf Department of Mathematics Jamia Millia Islamia New Delhi110025 India Department of Applied Sciences and Humanities Jamia Millia Islamia New Delhi110025 India Department of Computer Science Jamia Millia Islamia New Delhi110025 India

ISBN: (纸本)9789811503719

As the connectivity of the people with the Internet is increasing the use of the healthcare system. Due to this technology, it is possible to save time and expenditure of the patients. In medical communication, security and privacy are an important concern. Authentication is the essential validating part of secure information and network communication. A mutual authentication scheme for cloud-assisted medical system is published by Mohit et al. (J Med Syst 41(4):50, 2017. https://***/10.1007/s10916-017-0699-2). We have examined this protocol and found some design flaws and security issues in cloud environment. This protocol is vulnerable in different steps and phases. The proposed work shows that Mohit et al. framework inefficient in different phases. Therefore, mutual authentication and session key could not possible in these phases in telecare medical information system (TMIS). Finally, we provide solutions of Mohit et al. scheme. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Cloud computing

HIGH DIMENSIONAL LOGISTIC REGRESSION UNDER NETWORK DEPENDENCE

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arXiv 2021年

作者： Mukherjee, Somabha Niu, Ziang Halder, Sagnik Bhattacharya, Bhaswar B. Michailidis, George Department of Statistics and Data Science National University of Singapore Singapore Applied Mathematics and Computational Science University of Pennsylvania Philadelphia United States Department of Statistics University of Florida Gainesville United States Department of Statistics and Data Science University of Pennsylvania Philadelphia United States Department of Statistics and Informatics Institute University of Florida Gainesville United States

Logistic regression is key method for modeling the probability of a binary outcome based on a collection of covariates. However, the classical formulation of logistic regression relies on the independent sampling assumption, which is often violated when the outcomes interact through an underlying network structure, such as over a temporal/spatial domain or on a social network. This necessitates the development of models that can simultaneously handle both the network ‘peer-effect’ (arising from neighborhood interactions) and the effect of (possibly) high-dimensional covariates. In this paper, we develop a framework for incorporating such dependencies in a high-dimensional logistic regression model by introducing a quadratic interaction term, as in the Ising model, designed to capture the pairwise interactions from the underlying network. The resulting model can also be viewed as an Ising model, where the node-dependent external fields linearly encode the high-dimensional covariates. We propose a penalized maximum pseudo-likelihood method for estimating the network peer-effect and the effect of the covariates (the regression coefficients), which, in addition to handling the high-dimensionality of the parameters, conveniently avoids the computational intractability of the maximum likelihood approach. Under various standard regularity conditions, we show that the corresponding estimate attains the classical high-dimensional rate of consistency. In particular, our results imply that even under network dependence it is possible to consistently estimate the model parameters at the same rate as in classical (independent) logistic regression, when the true parameter is sparse and the underlying network is not too dense. Consequently, we derive the rates of consistency of our proposed estimator for various natural graph ensembles, such as bounded degree graphs, sparse Erdős-Rényi random graphs, and stochastic block models. We also develop an efficient algorithm for computin

关键词： Logistic regression

Challenges in reliable solar panel selection using MCDA methods

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Procedia computer science 2021年 192卷 4913-4923页

作者： Volodymir Kozlov Wojciech Sałabun Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. Żołnierska 49 71-210 Szczecin Poland

The alternative sources of energy have significantly improved quality and are more prevalent in recent years. Solar panels as one of these energy sources continue to be chosen for commercial and private usage. One of the more complex decisions is to choose components to installed in the solar system. All of the public available solar panels have eight important characteristics related to electricity efficiency and dimensions. However, there are many possible alternatives, so it is hard to say which one will be the most proper choice. MCDA methods can make this complex decision problem. This work presents an assessment of solar panels obtained by two popular MCDA methods, i.e., the COMET and TOPSIS techniques. Both methods are distance-based MCDA methods which are using characteristic points idea. However, the COMET method is the rank reversal phenomenon free method and return more accurate results. Next, we present a comparison to find the most rational solar panel from the defined set of alternatives considered their criteria. For this purpose, the weights vector is determined by using three methods. Therefore, results are determined based not only on the used MCDA method but also on the applied weights of the criteria.

关键词： TOPSIS COMET MCDA solar panels